Abstract
This paper reviewed a set of twenty-one original and innovative papers included in a special issue on UAVs for vegetation monitoring, which proposed new methods and techniques applied to diverse agricultural and forestry scenarios. Three general categories were considered: (1) sensors and vegetation indices used, (2) technological goals pursued, and (3) agroforestry applications. Some investigations focused on issues related to UAV flight operations, spatial resolution requirements, and computation and data analytics, while others studied the ability of UAVs for characterizing relevant vegetation features (mainly canopy cover and crop height) or for detecting different plant/crop stressors, such as nutrient content/deficiencies, water needs, weeds, and diseases. The general goal was proposing UAV-based technological solutions for a better use of agricultural and forestry resources and more efficient production with relevant economic and environmental benefits.
Highlights
Global plant production faces the major challenge of sustainability under the constraint of a rapidly growing world population and the gradual depletion of natural resources.In this context, remote sensing can play a fundamental role in changing the production model by developing and implementing new technologies for vegetation monitoring that will lead to higher yields, while obtaining more sustainable and environmentally friendly food and plant products [1]
The unmanned aerial vehicles (UAVs) or drones have demonstrated their suitability for timely tracking and assessment of vegetation status due to several advantages, as follows: (1) they can operate at low altitudes to provide aerial imagery with ultra-high spatial resolution allowing detection of fine details of vegetation, (2) the flights can be scheduled with great flexibility according to critical moments imposed by vegetation progress over time, (3) they can use diverse sensors and perception systems acquiring different ranges of vegetation spectrum, (4) this technology can generate digital surface models (DSMs) with three-dimensional (3D)
The results indicated that both solar zenith angle (SZA) and time of day (TOD)—which is logical since SZAs depend on the TOD—had the most significant impact on estimated NDVI values following a directly proportional relation
Summary
Global plant production faces the major challenge of sustainability under the constraint of a rapidly growing world population and the gradual depletion of natural resources. The SI includes the recent scientific contributions organized according to three general categories: (1) type of the sensor employed and, vegetation index (VI) applied, (2) technological goals pursued, in terms of UAV configuration and specifications, and issues related to image spatial resolution, computation, artificial intelligence, and image processing algorithms, and (3) agroforestry applications, which involved novel UAV-based data-driven approaches for monitoring vegetation features in certain critical dates, measuring plant trails over time for crop dynamics studies, and detecting and modeling biotic (weeds, disease) and abiotic (water, nutrition deficiencies) stress factors These three categories shared the common objective of proposing new methods and techniques to achieve better use of agricultural and forestry resources and more efficient production with relevant economic and environmental benefits
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